Cell Samples Analytics

Dataset statistics

Number of variables	11
Number of observations	699
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	8
Duplicate rows (%)	1.1%
Total size in memory	60.2 KiB
Average record size in memory	88.2 B

Variable types

NUM	9
CAT	2

Reproduction

Analysis started	2020-06-04 12:03:57.845005
Analysis finished	2020-06-04 12:04:34.688440
Duration	36.84 seconds
Version	pandas-profiling v2.8.0
Command line	`pandas_profiling --config_file config.yaml [YOUR_FILE.csv]`
Download configuration	config.yaml

Warnings

Dataset has 8 (1.1%) duplicate rows	Duplicates
`UnifShape` is highly correlated with `UnifSize`	High correlation
`UnifSize` is highly correlated with `UnifShape`	High correlation

ID
Real number (ℝ_≥0)

Distinct count	645
Unique (%)	92.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1071704.0987124464
Minimum	61634
Maximum	13454352
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	61634
5-th percentile	411453
Q1	870688.5
median	1171710
Q3	1238298
95-th percentile	1333890.8
Maximum	13454352
Range	13392718
Interquartile range (IQR)	367609.5

Descriptive statistics

Standard deviation	617095.7298
Coefficient of variation (CV)	0.5758079404
Kurtosis	257.7171591
Mean	1071704.099
Median Absolute Deviation (MAD)	104381
Skewness	13.67532594
Sum	749121165
Variance	3.808071398e+11

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1182404	6	0.9%
1276091	5	0.7%
1198641	3	0.4%
466906	2	0.3%
1116116	2	0.3%
1070935	2	0.3%
385103	2	0.3%
1293439	2	0.3%
1240603	2	0.3%
1277792	2	0.3%
Other values (635)	671	96.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
61634	1	0.1%
63375	1	0.1%
76389	1	0.1%
95719	1	0.1%
128059	1	0.1%

Value	Count	Frequency (%)
13454352	1	0.1%
8233704	1	0.1%
1371920	1	0.1%
1371026	1	0.1%
1369821	1	0.1%

Clump
Real number (ℝ_≥0)

Distinct count	10
Unique (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	4.417739628040057
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	4
Q3	6
95-th percentile	10
Maximum	10
Range	9
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.815740659
Coefficient of variation (CV)	0.6373713473
Kurtosis	-0.6237154123
Mean	4.417739628
Median Absolute Deviation (MAD)	2
Skewness	0.5928585327
Sum	3088
Variance	7.928395456

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	145	20.7%
5	130	18.6%
3	108	15.5%
4	80	11.4%
10	69	9.9%
2	50	7.2%
8	46	6.6%
6	34	4.9%
7	23	3.3%
9	14	2.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	145	20.7%
2	50	7.2%
3	108	15.5%
4	80	11.4%
5	130	18.6%

Value	Count	Frequency (%)
10	69	9.9%
9	14	2.0%
8	46	6.6%
7	23	3.3%
6	34	4.9%

UnifSize
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	10
Unique (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.13447782546495
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	5
95-th percentile	10
Maximum	10
Range	9
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	3.05145911
Coefficient of variation (CV)	0.9735143395
Kurtosis	0.09880288537
Mean	3.134477825
Median Absolute Deviation (MAD)	0
Skewness	1.233136558
Sum	2191
Variance	9.3114027

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	384	54.9%
10	67	9.6%
3	52	7.4%
2	45	6.4%
4	40	5.7%
5	30	4.3%
8	29	4.1%
6	27	3.9%
7	19	2.7%
9	6	0.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	384	54.9%
2	45	6.4%
3	52	7.4%
4	40	5.7%
5	30	4.3%

Value	Count	Frequency (%)
10	67	9.6%
9	6	0.9%
8	29	4.1%
7	19	2.7%
6	27	3.9%

UnifShape
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	10
Unique (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.207439198855508
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	5
95-th percentile	10
Maximum	10
Range	9
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.971912767
Coefficient of variation (CV)	0.9265686995
Kurtosis	0.007010980047
Mean	3.207439199
Median Absolute Deviation (MAD)	0
Skewness	1.161859179
Sum	2242
Variance	8.832265496

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	353	50.5%
2	59	8.4%
10	58	8.3%
3	56	8.0%
4	44	6.3%
5	34	4.9%
7	30	4.3%
6	30	4.3%
8	28	4.0%
9	7	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	353	50.5%
2	59	8.4%
3	56	8.0%
4	44	6.3%
5	34	4.9%

Value	Count	Frequency (%)
10	58	8.3%
9	7	1.0%
8	28	4.0%
7	30	4.3%
6	30	4.3%

MargAdh
Real number (ℝ_≥0)

Distinct count	10
Unique (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2.8068669527896994
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	4
95-th percentile	10
Maximum	10
Range	9
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.855379239
Coefficient of variation (CV)	1.017283429
Kurtosis	0.9879470695
Mean	2.806866953
Median Absolute Deviation (MAD)	0
Skewness	1.524468091
Sum	1962
Variance	8.1531906

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	407	58.2%
3	58	8.3%
2	58	8.3%
10	55	7.9%
4	33	4.7%
8	25	3.6%
5	23	3.3%
6	22	3.1%
7	13	1.9%
9	5	0.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	407	58.2%
2	58	8.3%
3	58	8.3%
4	33	4.7%
5	23	3.3%

Value	Count	Frequency (%)
10	55	7.9%
9	5	0.7%
8	25	3.6%
7	13	1.9%
6	22	3.1%

SingEpiSize
Real number (ℝ_≥0)

Distinct count	10
Unique (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.216022889842632
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	4
95-th percentile	8
Maximum	10
Range	9
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.214299887
Coefficient of variation (CV)	0.6885211836
Kurtosis	2.169066423
Mean	3.21602289
Median Absolute Deviation (MAD)	0
Skewness	1.712171802
Sum	2248
Variance	4.903123988

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2	386	55.2%
3	72	10.3%
4	48	6.9%
1	47	6.7%
6	41	5.9%
5	39	5.6%
10	31	4.4%
8	21	3.0%
7	12	1.7%
9	2	0.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	47	6.7%
2	386	55.2%
3	72	10.3%
4	48	6.9%
5	39	5.6%

Value	Count	Frequency (%)
10	31	4.4%
9	2	0.3%
8	21	3.0%
7	12	1.7%
6	41	5.9%

BareNuc
Categorical

Distinct count	11
Unique (%)	1.6%
Missing	0
Missing (%)	0.0%
Memory size	5.5 KiB

1	402
10	132
5	30
2	30
3	28
Other values (6)	77

Common Values
Length

Value	Count	Frequency (%)
1	402	57.5%
10	132	18.9%
5	30	4.3%
2	30	4.3%
3	28	4.0%
8	21	3.0%
4	19	2.7%
?	16	2.3%
9	9	1.3%
7	8	1.1%

Length

Max length	2
Median length	1
Mean length	1.188841202
Min length	1

BlandChrom
Real number (ℝ_≥0)

Distinct count	10
Unique (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.4377682403433476
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	5
95-th percentile	8
Maximum	10
Range	9
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.438364252
Coefficient of variation (CV)	0.7092869798
Kurtosis	0.1846213115
Mean	3.43776824
Median Absolute Deviation (MAD)	1
Skewness	1.099969082
Sum	2403
Variance	5.945620227

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2	166	23.7%
3	165	23.6%
1	152	21.7%
7	73	10.4%
4	40	5.7%
5	34	4.9%
8	28	4.0%
10	20	2.9%
9	11	1.6%
6	10	1.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	152	21.7%
2	166	23.7%
3	165	23.6%
4	40	5.7%
5	34	4.9%

Value	Count	Frequency (%)
10	20	2.9%
9	11	1.6%
8	28	4.0%
7	73	10.4%
6	10	1.4%

NormNucl
Real number (ℝ_≥0)

Distinct count	10
Unique (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2.866952789699571
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	4
95-th percentile	10
Maximum	10
Range	9
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	3.053633894
Coefficient of variation (CV)	1.065114816
Kurtosis	0.4742686755
Mean	2.86695279
Median Absolute Deviation (MAD)	0
Skewness	1.422261257
Sum	2004
Variance	9.324679956

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	443	63.4%
10	61	8.7%
3	44	6.3%
2	36	5.2%
8	24	3.4%
6	22	3.1%
5	19	2.7%
4	18	2.6%
9	16	2.3%
7	16	2.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	443	63.4%
2	36	5.2%
3	44	6.3%
4	18	2.6%
5	19	2.7%

Value	Count	Frequency (%)
10	61	8.7%
9	16	2.3%
8	24	3.4%
7	16	2.3%
6	22	3.1%

Mit
Real number (ℝ_≥0)

Distinct count	9
Unique (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.5894134477825466
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	5.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	5
Maximum	10
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.715077943
Coefficient of variation (CV)	1.07906344
Kurtosis	12.65787807
Mean	1.589413448
Median Absolute Deviation (MAD)	0
Skewness	3.560657844
Sum	1111
Variance	2.941492349

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	579	82.8%
2	35	5.0%
3	33	4.7%
10	14	2.0%
4	12	1.7%
7	9	1.3%
8	8	1.1%
5	6	0.9%
6	3	0.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	579	82.8%
2	35	5.0%
3	33	4.7%
4	12	1.7%
5	6	0.9%

Value	Count	Frequency (%)
10	14	2.0%
8	8	1.1%
7	9	1.3%
6	3	0.4%
5	6	0.9%

Class
Categorical

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.5 KiB

2	458
4	241

Common Values
Length

Value	Count	Frequency (%)
2	458	65.5%
4	241	34.5%

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

First rows

	ID	Clump	UnifSize	UnifShape	MargAdh	SingEpiSize	BareNuc	BlandChrom	NormNucl	Mit	Class
0	1000025	5	1	1	1	2	1	3	1	1	2
1	1002945	5	4	4	5	7	10	3	2	1	2
2	1015425	3	1	1	1	2	2	3	1	1	2
3	1016277	6	8	8	1	3	4	3	7	1	2
4	1017023	4	1	1	3	2	1	3	1	1	2
5	1017122	8	10	10	8	7	10	9	7	1	4
6	1018099	1	1	1	1	2	10	3	1	1	2
7	1018561	2	1	2	1	2	1	3	1	1	2
8	1033078	2	1	1	1	2	1	1	1	5	2
9	1033078	4	2	1	1	2	1	2	1	1	2

Last rows

	ID	Clump	UnifSize	UnifShape	MargAdh	SingEpiSize	BareNuc	BlandChrom	NormNucl	Mit	Class
689	654546	1	1	1	1	2	1	1	1	8	2
690	654546	1	1	1	3	2	1	1	1	1	2
691	695091	5	10	10	5	4	5	4	4	1	4
692	714039	3	1	1	1	2	1	1	1	1	2
693	763235	3	1	1	1	2	1	2	1	2	2
694	776715	3	1	1	1	3	2	1	1	1	2
695	841769	2	1	1	1	2	1	1	1	1	2
696	888820	5	10	10	3	7	3	8	10	2	4
697	897471	4	8	6	4	3	4	10	6	1	4
698	897471	4	8	8	5	4	5	10	4	1	4

Most frequent

	ID	Clump	UnifSize	UnifShape	MargAdh	SingEpiSize	BareNuc	BlandChrom	NormNucl	Mit	Class	count
0	320675	3	3	5	2	3	10	7	1	1	4	2
1	466906	1	1	1	1	2	1	1	1	1	2	2
2	704097	1	1	1	1	1	1	2	1	1	2	2
3	1100524	6	10	10	2	8	10	7	3	3	4	2
4	1116116	9	10	10	1	10	8	3	3	1	4	2
5	1198641	3	1	1	1	2	1	3	1	1	2	2
6	1218860	1	1	1	1	1	1	3	1	1	2	2
7	1321942	5	1	1	1	2	1	3	1	1	2	2

Overview

Variables

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows

Duplicate rows

Most frequent